Comparing two binary diagnostic tests with repeated measurements

We compare two binary diagnostic tests when each subject is measured more than once with each test and with a gold standard. We introduce a new model that allows the correlation between two measurements on a single subject by the same test to be different from the correlation between two measurements by different tests. We show that moment estimators of the population parameters for the mean sensitivities and specificities are virtually identical to the maximum likelihood estimates from our random-effects model. We apply the model to data comparing two rapid malaria tests and provide guidance for choosing the number of subjects and repeated measurements.